On structural contraction of biological interaction networks

Fuente: arXiv
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Main Authors: Al-Radhawi, M. Ali, Angeli, David, Sontag, Eduardo
Format: Preprint
Published: 2023
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author Al-Radhawi, M. Ali
Angeli, David
Sontag, Eduardo
author_facet Al-Radhawi, M. Ali
Angeli, David
Sontag, Eduardo
contents Biological networks are customarily described as structurally robust. This means that they often function extremely well under large forms of perturbations affecting both the concentrations and the kinetic parameters. In order to explain this property, various mathematical notions have been proposed in the literature. In this paper, we propose the notion of structural contractivity, building on the previous work of the authors. That previous work characterized the long-term dynamics of classes of Biological Interaction Networks (BINs), based on "rate-dependent Lyapunov functions". Here, we show that stronger notions of convergence can be established by proving structural contractivity with respect to non-standard polyhedral $\ell_\infty$-norms. In particular, we show that such networks are nonexpansive. With additional verifiable conditions, we show that they are strictly contractive over arbitrary positive compact sets. In addition, we show that such networks entrain to periodic inputs. We illustrate our theory with examples drawn from the modeling of intracellular signaling pathways.
format Preprint
id arxiv_https___arxiv_org_abs_2307_13678
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle On structural contraction of biological interaction networks
Al-Radhawi, M. Ali
Angeli, David
Sontag, Eduardo
Optimization and Control
Dynamical Systems
Molecular Networks
93D05, 80A30, 47H09, 37B25, 05C90, 92B99, 34A34, 34D30, 37C20
Biological networks are customarily described as structurally robust. This means that they often function extremely well under large forms of perturbations affecting both the concentrations and the kinetic parameters. In order to explain this property, various mathematical notions have been proposed in the literature. In this paper, we propose the notion of structural contractivity, building on the previous work of the authors. That previous work characterized the long-term dynamics of classes of Biological Interaction Networks (BINs), based on "rate-dependent Lyapunov functions". Here, we show that stronger notions of convergence can be established by proving structural contractivity with respect to non-standard polyhedral $\ell_\infty$-norms. In particular, we show that such networks are nonexpansive. With additional verifiable conditions, we show that they are strictly contractive over arbitrary positive compact sets. In addition, we show that such networks entrain to periodic inputs. We illustrate our theory with examples drawn from the modeling of intracellular signaling pathways.
title On structural contraction of biological interaction networks
topic Optimization and Control
Dynamical Systems
Molecular Networks
93D05, 80A30, 47H09, 37B25, 05C90, 92B99, 34A34, 34D30, 37C20
url https://arxiv.org/abs/2307.13678